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README.md
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---
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license: mit
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base_model: microsoft/deberta-v3-base
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: deberta-v3-base-lora-isarcasm
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# deberta-v3-base-lora-isarcasm
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6943
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- Accuracy: 0.1770
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- F1: 0.3008
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- Precision: 0.1770
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- Recall: 1.0
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.005
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- train_batch_size: 64
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| No log | 1.0 | 54 | 0.7069 | 0.8286 | 0.0 | 0.0 | 0.0 |
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| No log | 2.0 | 108 | 0.6931 | 0.8286 | 0.0 | 0.0 | 0.0 |
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| No log | 3.0 | 162 | 0.6986 | 0.8286 | 0.0 | 0.0 | 0.0 |
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| No log | 4.0 | 216 | 0.6946 | 0.1714 | 0.2927 | 0.1714 | 1.0 |
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| No log | 5.0 | 270 | 0.6939 | 0.1714 | 0.2927 | 0.1714 | 1.0 |
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### Framework versions
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- Transformers 4.32.0
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- Pytorch 2.1.1+cu121
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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